Human-Centred AI: First Steps for the Enrichment of Library Work

by Athanasios Mazarakis and Isabella Peters

“What is critical for human-centered AI at work? – Toward an interdisciplinary theory” is the title of a recently published article in which Dr Athanasios Mazarakis and Prof. Dr Isabella Peters from the ZBW – Leibniz Information Centre for Economics were involved.

Here they summarise the implications for future work in libraries.

Human-centred AI

The article emphasises the importance of human-centred AI (HCAI) in the workplace and proposes an interdisciplinary theory to achieve this goal. We have drawn conclusions for HCAI in the workplace by using insights from disciplines that focus mainly on individuals (psychology), technology (HCI), work (HFE) or the work context as one research field among many (information science and adult learning). Theoretical and practical implications are derived from the basic disciplinary considerations and the current experiences and observations from the Federal Ministry of Education and Research funded project CoCo-Projekt (German, Connect & Collect: AI-supported cloud for interdisciplinary networked research and innovation for future work) in order to harmonise HCAI with the current requirements of employees and companies, which place people at the centre when dealing with the complexity of information, data and decisions.

Utilising interdisciplinary theories and methods for integration in libraries

For library staff, this means that the integration of human-centred AI should be at the forefront of the development of work and training. This can be achieved by incorporating interdisciplinary theories and methods that focus on people, technology, work and the work context.

First steps towards human-centred AI in libraries

A useful first step for librarians would be to familiarise themselves with the interdisciplinary theories and methods proposed in this article. Then they can assess how these theories and methods can be applied to their work and training. In addition, librarians can collaborate with other professionals from related fields to gain a broader interdisciplinary perspective on the topic. In detail, the three aspects are organised as follows:

1. Incorporate user-centred design principles: Library staff can apply user-centred design principles to ensure that AI systems are developed with the needs and preferences of users in mind – people who borrow literature, for example. This can include conducting user research to understand the needs and preferences of library users and using this information to design AI systems that are intuitive and easy to use.
2. Developing AI expertise: Librarians can develop AI skills to better understand the capabilities and limitations of AI systems. This can include learning about the different types of AI systems, how they work and how they can be used to improve library services. By developing AI skills, librarians can make informed decisions about the use of AI in their work and ensure that AI systems are used in a responsible and ethical manner.
3. Collaboration with other experts: Librarians can collaborate with other professionals from related fields to gain a broader interdisciplinary perspective on the topic of human-centred AI. This may include working with experts from the fields of psychology, human-computer interaction, information science and adult education to develop a broader understanding of the impact of AI on library services. By collaborating with other professionals, librarians can ensure that their work is based on the latest research results and best practices in the field of human-centred AI.

Accompanying measures and framework conditions for human-centred AI in libraries

In addition, the observance of transparency and data protection of AI in library services is an ethical aspect for library staff to work on. Furthermore, further training and the development of training materials are relevant points for the communication of human-centred AI by libraries. Along with this, librarians should ask stakeholders about their needs and preferences regarding AI systems. Finally, relevant AI systems should be observed and evaluated by libraries. Specifically, this means the following:

4. Develop ethical guidelines: Librarians can develop ethical guidelines for the use of AI in library services. This can include establishing principles for the responsible use of AI, such as ensuring transparency and accountability in decision-making, protecting user privacy, and avoiding bias and discrimination. By developing ethical guidelines, librarians can ensure that AI systems are used in a way that is consistent with the library’s values and mission.
5. Provide training and support: Librarians can offer training and support to library staff and users in the use of AI systems. This can include developing training materials, offering workshops and webinars, and providing one-on-one support to users who need help. By providing training and support, librarians can ensure that AI systems are used effectively and efficiently and that users feel comfortable and safe using them.
6. Involvement of stakeholders: Librarians can engage with stakeholders (users and librarians at other libraries) to gather feedback and suggestions on the use of AI in library services. This can include organising focus groups, conducting surveys and collecting feedback via social media and other channels. By engaging stakeholders, librarians can ensure that AI systems are designed and deployed in a way that reflects the needs and preferences of stakeholders.
7. Monitoring and evaluation of AI systems: Librarians can monitor and evaluate AI systems to ensure they are working as intended and delivering the desired results. This can include analysing usage data, conducting tests with users and gathering feedback from library staff and users. By monitoring and evaluating AI systems, librarians can identify areas for improvement and make adjustments as needed.

Improving library work through the integration of human-centred AI

In summary, the Frontiers article “What is critical for human-centered AI at work? – Toward an interdisciplinary theory” provides valuable insights for the development of work and training in libraries. By prioritising the integration of human-centred AI, focusing on the human element and incorporating interdisciplinary theories and methods, library staff can improve their work. There is a variety of applications in the library context that can be or are already being automated: Chatbots, cataloguing, classification, recommendation systems, personalised recommendations, inventory management, text and image recognition as well as text analysis and generation. This shows how important human-centred AI already is today. Its potential for the future is hinted at in the article. In any case, it will be exciting to see how further developments in the library sector will unfold!

Original article: What is critical for human-centered AI at work? – Toward an interdisciplinary theory”.

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